Abstract
Our current understanding of the determinants of plasma proteome variation during pediatric development remains incomplete. Here, we show that genetic variants, age, sex and body mass index significantly influence this variation. Using a streamlined and highly quantitative mass spectrometry-based proteomics workflow, we analyzed plasma from 2,147 children and adolescents, identifying 1,216 proteins after quality control. Notably, the levels of 70% of these were associated with at least one of the aforementioned factors, with protein levels also being predictive. Quantitative trait loci (QTLs) regulated at least one-third of the proteins; between a few percent and up to 30-fold. Together with excellent replication in an additional 1,000 children and 558 adults, this reveals substantial genetic effects on plasma protein levels, persisting from childhood into adulthood. Through Mendelian randomization and colocalization analyses, we identified 41 causal genes for 33 cardiometabolic traits, emphasizing the value of protein QTLs in drug target identification and disease understanding.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Nature Genetics |
| Vol/bind | 57 |
| Sider (fra-til) | 635–646 |
| ISSN | 1061-4036 |
| DOI | |
| Status | Udgivet - 2025 |
Bibliografisk note
Funding Information:Our gratitude goes to all participants and their families from The HOLBAEK Study. We appreciate the staff at The Children\u2019s Obesity Clinic for their assistance in clinical studies, especially G. Holl\u00F8se and T. Larsen for providing the state of the acquisition, storage and maintenance of biological samples and clinical data. J. Bork-Jensen and J. V. T. Lominchar at the Phenomics Platform of Novo Nordisk Foundation Center for Basic Metabolic Research deserve recognition for their genomics data processing contributions. We also acknowledge the members of the Clinical Proteomics Group at Novo Nordisk Foundation Center for Protein Research and the Department of Proteomics and Signal Transduction (Max Planck Institute of Biochemistry). Special thanks to L. Drici, V. Albrecht and A. Brunner for their technical assistance. J. Madsen and M. Wierer, Director of Proteomics Research Infrastructure (PRI), provided valuable technical support as well. Our appreciation extends to V. Gudmundsdottir at the University of Iceland for kindly sharing the pQTL results she had collected from 20 existing pQTL studies, and to L. Folkersen at Nucleus and Tobias Nyholm Wistisen at Novo Nordisk for technical discussions. The research reported in this publication was supported in part by Novo Nordisk Fonden under grant nos. NNF15CC0001 (to M.M.), NNF15OC0016692 (to the MicrobLiver Consortium), NNF15OC0016544 (to T.H.), NNF14CC0001 and NNF21SA0072102 (to S.R.), NNF20OC0059393 (to M.T.), NNF18SA0034956 (to C.E.F.) and NNF20SA0067242 (to L.A.H.); Innovationsfonden under grant no. 0603-00484B (to T.H.); Horizon 2020 Framework Programme under grant no. 668031 (to the GALAXY Consortium); Region Zealand Health and Medical Research Foundation under grant no. R32-A1191 (to C.E.F.); and the Danish Heart Foundation under grant no. PhD2023009-HF (to L.A.H.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Publisher Copyright:
© The Author(s) 2025.